OCRSpell: an interactive spelling correction system for OCR errors in text

摘要

In this paper, we describe a spelling correc- tion system designed specifically for OCR-generated text that selects candidate words through the user of infor- mation gathered from multiple knowledge sources. This system for text correction is based on static and dynamic device mappings, approximate string matching, and n- gram analysis. Our statistically based, Bayesian system incorporates a learning features that collects confusion information at the collection and document levels. An evaluation on the new system is presented as well.